Evaluation of radiation protection effectivity in a cardiac angiography room using visualized scattered radiation distribution.

In this study, we devised a radiation protection tool specifically designed for healthcare professionals and students engaged in cardiac catheterization to easily monitor and evaluate scattered radiation distribution across diverse C-arm angles and arbitrary physician associated staff positions - scrub nurse, technologist positions. In this study, scattered radiation distributions in an angiography room were calculated using the Monte Carlo simulation of PHITS code. Four visualizations were performed under different C-arm angles with and without radiation protection: 1) a dose profile, 2) a 2D cross-section, 3) a 3D scattered radiation distribution, and 4) a 4D scattered radiation distribution. The simulation results detailing the scattered radiation distribution in PHITS were exported in Visualization Toolkit (vtk) format and visualized through the open-source visualization application ParaView for analysis. Visualization of the scattered dose showed that dose distribution depends on the C-arm angle and the X-ray machine output parameters (kV, mAs/second, beam filtration) which depend upon beam angulation to the patient body. When irradiating in the PA direction, the protective curtain decreased the dose by 62% at a point 80 cm from the floor, where the physician's gonads are positioned. Placing the protection board close to the X-ray tube reduced the dose by 24% at a location 160 cm from the floor, where the lens of the eye is situated. Notably, positioning the protection board adjacent to the physician resulted in a 95.4% reduction in incident air kerma. These visualization displays can be combined to understand the spread and direction of the scattered radiation distribution and to determine where and how to operate and place radiation protection devices, accounting for the different beam angulations encountered in interventional cases. This study showed that scatter visualization could be a radiation protection teaching aid for students and medical staff in angiography rooms.

Automated development of the contrast-detail curve based on statistical low-contrast detectability in CT images.

PURPOSE: We have developed a software to automatically find the contrast-detail (C-D) curve based on the statistical low-contrast detectability (LCD) in images of computed tomography (CT) phantoms at multiple cell sizes and to generate minimum detectable contrast (MDC) characteristics. METHODS: A simple graphical user interface was developed to set the initial parameters needed to create multiple grid region of interest of various cell sizes with a 2-pixel increment. For each cell in the grid, the average CT number was calculated to obtain the standard deviation (SD). Detectability was then calculated by multiplying the SD of the mean CT numbers by 3.29. This process was automatically repeated as many times as the cell size was set at initialization. Based on the obtained LCD, the C-D curve was obtained and the target size at an MDC of 0.6% (i.e., 6-HU difference) was determined. We subsequently investigated the consistency of the target sizes for a 0.6% MDC at four locations within the homogeneous image. We applied the software to images with six noise levels, images of two modules of the American College of Radiology CT phantom, images of four different phantoms, and images of four different CT scanners. We compared the target sizes at a 0.6% MDC based on the statistical LCD and the results from a human observer. RESULTS: The developed system was able to measure C-D curves from different phantoms and scanners. We found that the C-D curves follow a power-law fit. We found that higher noise levels resulted in a higher MDC for a target of the same size. The low-contrast module image had a slightly higher MDC than the distance module image. The minimum size of an object detected by visual observation was slightly larger than the size using statistical LCD. CONCLUSIONS: The statistical LCD measurement method can generate a C-D curve automatically, quickly, and objectively.

Automated procedure for slice thickness verification of computed tomography images: Variations of slice thickness, position from iso-center, and reconstruction filter.

PURPOSE: The purpose of this study is to automate the slice thickness verification on the AAPM CT performance phantom and validate it for variations of slice thickness, position from iso-center, and reconstruction filter. METHODS: An automatic procedure for slice thickness verification on AAPM CT performance phantom was developed using MATLAB R2015b. The stair object image within the phantom was segmented, and the middle stair object was located. Its angle was determined using the Hough transformation, and the image was rotated accordingly. The profile through this object was obtained, and its full-width of half maximum (FWHM) was automatically measured. The FWHM indicated the slice thickness of the image. The automated procedure was applied with variations in three independent parameters, i.e., the slice thickness, the distance from the phantom to the iso-center, and the reconstruction filter. The automated results were compared to manual measurements made using electronic calipers. RESULTS: The differences of the automated results from the nominal slice thicknesses were within 1.0 mm. The automated results are comparable to those from manual approach (i.e., the difference of both is within 12%). The automatic procedure accurately obtained slice thickness even when the phantom was moved from the iso-center position by up to 4 cm above and 4 cm below the iso-center. The automated results were similar (to within 0.1 mm) for various reconstruction filters. CONCLUSIONS: We successfully developed an automated procedure of slice thickness verification and confirmed that the automated procedure provided accurate results. It provided an easy and effective method of determining slice thickness.

An improved method for automated calculation of the water-equivalent diameter for estimating size-specific dose in CT.

PURPOSE: The aim of this study is to propose an algorithm for the automated calculation of water-equivalent diameter (Dw ) and size-specific dose estimation (SSDE) from clinical computed tomography (CT) images containing one or more substantial body part. METHODS: All CT datasets were retrospectively acquired by the Toshiba Aquilion 128 CT scanner. The proposed algorithm consisted of a contouring stage for the Dw calculation, carried out by taking the six largest objects in the cross-sectional image of the patient's body, followed by the removal of the CT table depending on the center position (y-axis) of each object. Validation of the proposed algorithm used images of patients who had undergone chest examination with both arms raised up, one arm placed down and both arms placed down, images of the pelvic region consisting of one substantial object, and images of the lower extremities consisting of two separated areas. RESULTS: The proposed algorithm gave the same results for Dw and SSDE as the previous algorithm when images consisted of one substantial body part. However, when images consisted of more than one substantial body part, the new algorithm was able to detect all parts of the patient within the image. The Dw values from the proposed algorithm were 9.5%, 15.4%, and 39.6% greater than the previous algorithm for the chest region with one arm placed down, both arms placed down, and images with two legs, respectively. The SSDE values from the proposed algorithm were 8.2%, 11.2%, and 20.6% lower than the previous algorithm for the same images, respectively. CONCLUSIONS: We have presented an improved algorithm for automated calculation of Dw and SSDE. The proposed algorithm is more general and gives accurate results for both Dw and SSDE whether the CT images contain one or more than one substantial body part.

Development of a head CT dose index (CTDI) phantom based on polyester resin and methyl ethyl ketone peroxide (MEKP): a preliminary study.

This paper aims to develop phantoms for measurement of computed tomography dose index (CTDI) based on a polyester resin mixed with methyl ethyl ketone peroxide (MEKP) as catalyst. CT number and CTDI values of the polyester resin phantoms were compared with a standard polymethyl methacrylate (PMMA) phantom as reference. The percentage of MEKP was varied from 0.3 to 0.6 wt%. The polyester resin phantoms had diameter of 160 mm, length of 150 mm and five cylindrical holes with diameter of 13.5 mm. One hole was positioned at the centre of the phantom and the other four near its periphery, 10 mm from the edge. The results show that the CT number of the polyester resin phantom was about 1%-9% higher than that of the standard PMMA phantom. Among the polyester resin phantoms, the one with 0.3 wt% MEKP is closest to the standard PMMA phantom in terms of CT number. In addition, the difference in weighted CTDI value between the 0.3 wt% polyester resin phantom and the PMMA is less than 5%. Thus, the 0.3 wt% polyester resin is potentially used as an alternative to the standard PMMA, with the advantage of a lower cost.

Comparison of central, peripheral, and weighted size-specific dose in CT.

The objective of this study is to determine X-ray dose distribution and the correlation between central, peripheral and weighted-centre peripheral doses for various phantom sizes and tube voltages in computed tomography (CT). We used phantoms developed in-house, with various water-equivalent diameters (Dw) from 8.5 up to 42.1 cm. The phantoms have one hole in the centre and four holes at the periphery. By using these five holes, it is possible to measure the size-specific central dose (Ds,c), peripheral dose (Ds,p), and weighted dose (Ds,w).The phantoms are scanned using a CT scanner (Siemens Somatom Definition AS), with the tube voltage varied from 80 up to 140 kVps. The doses are measured using a pencil ionization chamber (Ray safe X2 CT Sensor) in every hole for all phantoms. The relationships between Ds,c, Ds,p, and Ds,w, and the water-equivalent diameter are established. The size-conversion factors are calculated. Comparisons between Ds,c, Ds,p, and Ds,ware also established. We observe that the dose is relatively homogeneous over the phantom for water-equivalent diameters of 12-14 cm. For water-equivalent diameters less than 12 cm, the dose in the centre is higher than at the periphery, whereas for water-equivalent diameters greater than 14 cm, the dose at the centre is lower than that at the periphery. We also find that the distribution of the doses is influenced by the tube voltage. These dose distributions may be useful for calculating organ doses for specific patients using their CT images in future clinical practice.

An evaluation of computed tomography dose index measurements using a pencil ionisation chamber and small detectors.

The aim of this study was to compare the values of the computed tomography dose index 100 (CTDI100) obtained using two small detectors (i.e. a small ionisation chamber and a small solid state detector) with those obtained from a 100 mm pencil ionisation chamber for various input CT parameters: beam width, kVp, mAs, pitch, and head-body phantom variation. The measurement of CTDI100 using the 100 mm pencil chamber was carried out in a single rotation of axial mode, while the measurement using small detectors was carried out in helical mode. The differences of CTDI100 values obtained with two small detectors were about 7% for all variations. The differences of CTDI100 values obtained with small detectors and a 100 mm pencil ionisation chamber for beam widths of more than 4 mm were within 40%. However, for the narrowest beam widths (4 mm), the difference between them was very large (about 150%).

Development of a novel artifact-free eye shield based on silicon rubber-lead composition in the CT examination of the head.

The aim of this work was to develop a novel artifact-free eye shield and evaluate its effect on the dose received by the eye lens and the resulting image quality in the CT examination of the head. A new material for an eye shield was synthesised from silicon rubber (SR) and lead (Pb) using a simple method. The percentage of Pb was varied from 0 to 5% wt. An anthropomorphic head phantom was scanned with and without the SR-Pb eye shield, and compared with a tungsten paper (WP) eye shield. The distance from the eye shield and head was varied from 0 to 5 cm. The dose to the eye lens was measured using photo-luminescence detectors (PLDs). The presence of artifacts was determined by measuring CT numbers at different eye lens locations and by subtracting images with and without the eye shield. The dose reduction increases with increasing Pb content in the SR-Pb eye shield. A 5% wt SR-Pb eye shield reduced the eye lens dose by up to 50%, whereas the WP eye shield reduced the dose by up to 86%. The CT numbers in images with the SR-Pb eye shield in the regions of both eyes and the center of the head phantom is similar to those without the eye shield, indicating that there is no artifact in the resulting image. Using the WP eye shield, there is considerable artifact with the CT number increasing by up to 700% in the regions of both eyes and the center of the head. It is found that the distance between the SR-Pb eye shield and the head does not affect either the dose or the resulting images. A SR-Pb-based eye shield can be applied in clinical environments and should be placed directly above the eye surface for dose optimisation.

Assessment of patient dose and noise level of clinical CT images: automated measurements.

We investigated comparisons between patient dose and noise in pelvic, abdominal, thoracic and head CT images using an automatic method. 113 patient images (37 pelvis, 34 abdominal, 25 thoracic, and 17 head examinations) were retrospectively and automatically examined in this study. Water-equivalent diameter (Dw), size-specific dose estimates (SSDE) and noise were automatically calculated from the center slice for every patient image. The Dw was calculated based on auto-contouring of the patients' edges, and the SSDE was calculated as the product of the volume CT dose index (CTDIvol) extracted from the Digital Imaging and Communications in Medicine (DICOM) header and the size conversion factor based on the Dw obtained from AAPM 204. The noise was automatically measured as a minimum standard deviation in the map of standard deviations. A square region of interest of about 1 cm2 was used in the automated noise measurement. The SSDE values for the pelvis, abdomen, thorax, and head were 21.8 ± 7.3 mGy, 22.0 ± 4.5 mGy, 21.5 ± 4.7 mGy, and 65.1 ± 1.7 mGy, respectively. The SSDEs for the pelvis, abdomen, and thorax increased linearly with increasing Dw, and for the head with constant tube current, the SSDE decreased with increasing Dw. The noise in the pelvis, abdomen, thorax, and head were 5.9 ± 1.5 HU, 5.2 ± 1.4 HU, 4.9 ± 0.8 HU and 3.9 ± 0.2 HU, respectively. The noise levels for the pelvis, abdomen, and thorax of the patients were relatively constant with Dw because of tube current modulation. The noise in the head image was also relatively constant because Dw variations in the head are very small. The automated approach provides a convenient and objective tool for dose optimizations.

An algorithm for automated modulation transfer function measurement using an edge of a PMMA phantom: Impact of field of view on spatial resolution of CT images.

PURPOSE: The purpose of this study was to introduce a new algorithm for automated measurement of the modulation transfer function (MTF) using an edge of a readily available phantom and to evaluate the effect of reconstruction filter and field of view (FOV) on the spatial resolution in the CT images. METHODS: Our automated MTF measurement consisted of several steps. The center of the image was established and an appropriate region of interest (ROI) designated. The edge spread function (ESF) was determined, and a suitably interpolated ESF curve was differentiated to obtain the line spread function (LSF). The LSF was Fourier transformed to obtain the MTF. All these steps were accomplished automatically without user intervention. The results of the automated MTF from the edge phantom were validated by comparing them with a point image, and the results of the automated calculation were validated by the standard fitting method. The automated MTF calculation was then applied to the images of two polymethyl methacrylate (PMMA) phantoms and a wire phantom which had been scanned by a Toshiba Alexion 4-slice CT scanner and reconstructed with various filter types and FOVs. RESULTS: The difference in the 50% MTF values obtained from the edge and point phantoms were within ±4%. The values from the automated and fitted methods agreed to within ±2%, indicating that the automated MTF calculation was accurate. The automated MTF calculation was able to differentiate MTF curves for various filters. The spatial resolution values were 0.37 ± 0.00, 0.71 ± 0.01, and 0.78 ± 0.01 cycles/mm for FC13, FC30 and FC52 filters, respectively. The spatial resolution of the images decrease linearly (R2  > 0.98) with increasing FOVs. CONCLUSION: An automated MTF method was successfully developed using an edge phantom, the PMMA phantom. The method is easy to implement in a clinical environment and is not influenced by user experience.

Automated Calculation of Water-equivalent Diameter (DW) Based on AAPM Task Group 220.

The purpose of this study is to accurately and effectively automate the calculation of the water-equivalent diameter (DW) from 3D CT images for estimating the size-specific dose. DW is the metric that characterizes the patient size and attenuation. In this study, DW was calculated for standard CTDI phantoms and patient images. Two types of phantom were used, one representing the head with a diameter of 16 cm and the other representing the body with a diameter of 32 cm. Images of 63 patients were also taken, 32 who had undergone a CT head examination and 31 who had undergone a CT thorax examination. There are three main parts to our algorithm for automated DW calculation. The first part is to read 3D images and convert the CT data into Hounsfield units (HU). The second part is to find the contour of the phantoms or patients automatically. And the third part is to automate the calculation of DW based on the automated contouring for every slice (DW,all). The results of this study show that the automated calculation of DW and the manual calculation are in good agreement for phantoms and patients. The differences between the automated calculation of DW and the manual calculation are less than 0.5%. The results of this study also show that the estimating of DW,all using DW,n=1 (central slice along longitudinal axis) produces percentage differences of -0.92% ± 3.37% and 6.75%± 1.92%, and estimating DW,all using DW,n=9 produces percentage differences of 0.23% ± 0.16% and 0.87% ± 0.36%, for thorax and head examinations, respectively. From this study, the percentage differences between normalized size-specific dose estimate for every slice (nSSDEall) and nSSDEn=1 are 0.74% ± 2.82% and -4.35% ± 1.18% for thorax and head examinations, respectively; between nSSDEall and nSSDEn=9 are 0.00% ± 0.46% and -0.60% ± 0.24% for thorax and head examinations, respectively.

A novel method for developing contrast-detail curves from clinical patient images based on statistical low-contrast detectability.

Purpose. To develop a method to extract statistical low-contrast detectability (LCD) and contrast-detail (C-D) curves from clinical patient images.Method. We used the region of air surrounding the patient as an alternative for a homogeneous region within a patient. A simple graphical user interface (GUI) was created to set the initial configuration for region of interest (ROI), ROI size, and minimum detectable contrast (MDC). The process was started by segmenting the air surrounding the patient with a threshold between -980 HU (Hounsfield units) and -1024 HU to get an air mask. The mask was trimmed using the patient center coordinates to avoid distortion from the patient table. It was used to automatically place square ROIs of a predetermined size. The mean pixel values in HU within each ROI were calculated, and the standard deviation (SD) from all the means was obtained. The MDC for a particular target size was generated by multiplying the SD by 3.29. A C-D curve was obtained by iterating this process for the other ROI sizes. This method was applied to the homogeneous area from the uniformity module of an ACR CT phantom to find the correlation between the parameters inside and outside the phantom, for 30 thoracic, 26 abdominal, and 23 head images.Results. The phantom images showed a significant linear correlation between the LCDs obtained from outside and inside the phantom, with R2values of 0.67 and 0.99 for variations in tube currents and tube voltages. This indicated that the air region outside the phantom can act as a surrogate for the homogenous region inside the phantom to obtain the LCD and C-D curves.Conclusion. The C-D curves obtained from outside the ACR CT phantom show a strong linear correlation with those from inside the phantom. The proposed method can also be used to extract the LCD from patient images by using the region of air outside as a surrogate for a region inside the patient.

A Practical Method for Slice Spacing Measurement Using the American Association of Physicists in Medicine Computed Tomography Performance Phantom.

Background: The slice spacing has a crucial role in the accuracy of computed tomography (CT) images in sagittal and coronal planes. However, there is no practical method for measuring the accuracy of the slice spacing. Purpose: This study proposes a novel method to automatically measure the slice spacing using the American Association of Physicists in Medicine (AAPM) CT performance phantom. Methods: The AAPM CT performance phantom module 610-04 was used to measure slice spacing. The process of slice spacing measurement involves a pair of axial images of the module containing ramp aluminum objects located at adjacent slice positions. The middle aluminum plate of each image was automatically segmented. Next, the two segmented images were combined to produce one image with two stair objects. The centroid coordinates of two stair objects were automatically determined. Subsequently, the distance between these two centroids was measured to directly indicate the slice spacing. For comparison, the slice spacing was calculated by accessing the slice position attributes from the DICOM header of both images. The proposed method was tested on phantom images with variations in slice spacing and field of view (FOV). Results: The results showed that the automatic measurement of slice spacing was quite accurate for all variations of slice spacing and FOV, with average differences of 9.0% and 9.3%, respectively. Conclusion: A new automated method for measuring the slice spacing using the AAPM CT phantom was successfully demonstrated and tested for variations of slice spacing and FOV. Slice spacing measurement may be considered an additional parameter to be checked in addition to other established parameters.

A challenge and solution for automatic thin slice thickness measurements on images of the Catphan phantom.

Purpose. The use of the Hough transform for angle detection is quite accurate for relatively wide slice thickness. However, the Hough transform fails to accurately detect the angle for thin slice thickness. This study proposes a method for automatically measuring the thickness of thin slices on images of a Catphan phantom.Methods. In the proposed method, the angle of the phantom's orientation was determined based on the relative coordinates of the four hole objects in the phantom. After the angles of the wires were determined, the profiles of pixel values across the wire objects were constructed. Finally, their full widths at half maximum (FWHMs) were determined and multiplied bytan23° to obtain the slice thicknesses of the images. The results of the proposed method were compared to a previous method, which used the Hough transform to obtain the phantom's orientation. We used slice thicknesses ranging from 0.8 mm to 5.0 mm, and phantom angles from 0° to 10°.Results. Our proposed method detected the angle of the phantom accurately for thin slices, whereas a previous method did not accurately detect the angle. The results of the slice thickness using this current method were slightly higher (within 7.9%) compared to the previous method. However, the results of the two methods did not differ significantly (p-value > 0.05). Using different angles, the current method detected all the angles more accurately. Again, the slice thicknesses were not significantly different from the previous method (p-value > 0.05).Conclusion. The proposed method for measuring the thickness of thin slices in an image of a Catphan phantom, based on the relative coordinates of the four hole objects in the phantom, outperformed a previous method based on the Hough transform.

Evaluation of direct point dose estimation based on the distribution of the size-specific dose estimate.

The aim of this study was to evaluate the point doses using a distribution of the size-specific dose estimate (SSDE) from axial CT images of in-house phantoms having diameters from 8 to 40 cm. In-house phantoms made of polyester-resin (PESR) mixed with methyl ethyl ketone peroxide (MEKP) were used. The phantoms were built with different diameter sizes of 8, 16, 24, 32, and 40 cm. The phantoms were scanned by Siemens a SOMATOM Perspective-128 slice CT scanner with constant input parameters. The point doses were interpolated from the central SSDE (SSDEc) and the peripheral SSDE (SSDEp). The SSDEc and SSDEp were calculated from the SSDE with h- and k-factors. The point doses were compared to the direct measurements using the nanoDot™ optically-stimulated luminescence dosimeter (OSLD) in dedicated holes on the phantoms. It was found that the point dose decreases as the phantom diameter increased. The doses obtained using two approaches differed by 11% on average. The highest difference was 40% and the lowest difference was < 1%. It was found that dose based on the SSDE concept tended to be higher compared to the measured dose by OSLD. Point dose estimation using the concept of SSDE distribution can be considered an alternative for accurate and simple estimation. This approach still requires improvements to increase its accuracy and its application to estimate the organ dose needs further investigation.

Estimation and comparison of the effective dose and lifetime attributable risk of thyroid cancer between males and females in routine head computed tomography scans: a multicentre study.

INTRODUCTION: A significant number of head computed tomography (CT) scans are performed annually. However, due to the close proximity of the thyroid gland to the radiation field, this procedure can expose the gland to ionising radiation. Consequently, this study aimed to estimate organ dose, effective dose (ED) and lifetime attributable risk (LAR) of thyroid cancer from head CT scans in adults. METHODS: Head CT scans of 74 patients (38 males and 36 females) were collected using three different CT scanners. Age, sex, and scanning parameters, including scan length, tube current-time product (mAs), pitch, CT dose index, and dose-length product (DLP) were collected. CT-Expo software was used to calculate thyroid dose and ED for each patient based on scan parameters. LARs were subsequently computed using the methodology presented in the Biologic Effects of Ionizing Radiation (BEIR) Phase VII report. RESULTS: Although the mean thyroid organ dose (2.66 ± 1.03 mGy) and ED (1.6 ± 0.4 mSv) were slightly higher in females, these differences were not statistically significant compared to males (mean thyroid dose, 2.52 ± 1.31 mGy; mean ED, 1.5 ± 0.4 mSv). Conversely, there was a significant difference between the mean thyroid LAR of females (0.91 ± 1.35) and males (0.20136 ± 0.29) (P = 0.001). However, the influencing parameters were virtually identical for both groups. CONCLUSIONS: The study's results indicate that females have a higher LAR than males, which can be attributed to higher radiation sensitivity of the thyroid in females. Thus, additional care in the choice of scan parameters and irradiated scan field for female patients is recommended.

Algorithm development for automatic laser alignment assessment on an ACR CT phantom and its evaluation on sixteen CT scanners.

Purpose. The aim of this study is to develop software to automatically assess the laser alignment on the ACR CT phantom and evaluate its accuracy on sixteen CT scanners.Methods. Software for an automated method of laser alignment assessment on the ACR CT phantom was developed. Laser alignment assessment was based on the positions of the ball-bearing markers at the edge of the ACR CT phantom. The automatic assessment was performed using several steps, including segmentation to acquire the coordinates of the ball-bearing markers and determination of the distances between lines connecting them with lines through the center of the image. A comparison of the results from the automatic method with those from the manual method was performed. The manual measurements were carried out using MicroDicom Viewer. A Mann-Whitney U test was performed to determine the statistical difference between both methods. The evaluation was performed on images of the ACR CT phantom scanned with 16 CT scanners from 5 different CT manufacturers.Results. The results confirmed that our software successfully segments the ball-bearing markers and determines the laser alignment assessment on the ACR CT phantom. Evaluation of the algorithm with images from the 16 CT scanners revealed that the difference between the results from automatic and manual methods were about 0.2 mm with apvalue of around 0.7 (no statistical difference). Misalignment in they-axis was larger than the misalignment in the x-axisfor the majority of the scanners tested. It was found that the phantom tended to be placed 2 mm higher than the iso-center.Conclusions. Software to automatically assess CT laser alignment with the ACR CT phantom was successfully developed and evaluated. The automatic assessment was comparable to manual assessment. In addition, the automatic method was user independent and fast.

Automatic measurement of slice thickness in CT images of a Siemens phantom.

This study aims to develop a program in Python language for automatic measurement of slice thickness in computed tomography (CT) images of a Siemens phantom with different values of slice thickness, field of view (FOV), and pitch. A Siemens phantom was scanned using a Siemens 64-slice Somatom Perspective CT scanner with various slice thicknesses (i.e. 2, 4, 6, 8, and 10 mm), FOVs (i.e. 220, 260, and 300 mm), and pitch (i.e. 0.7, 0.9, and 1). Automatic measurement of slice thickness was performed by segmenting the ramp insert in the image and detecting angles of the ramp insert using the Hough transform. The resulting angles were subsequently used to rotate the image. Profiles of pixel along the ramp insert were made from the rotated images, and the slice thickness was calculated by determining the full-width at half maximum (FWHM) of the profiles. The product of the FWHM in pixels and the pixel size was corrected by the tangent of the ramp insert (i.e., 23°) to obtain the measured slice thickness. The results of the automatic measurements were compared with manual measurements carried out using a MicroDicom Viewer. The differences between the automatic and manual measurements at all slice thicknesses were less than 0.30 mm. The automatic and manual measurements had high linear correlations. For variations of the FOV and pitch, the differences between the automatic and manual measurement were less than 0.16 mm. The automatic and manual measurements were significantly different (p-value < 0.05) for slice thickness variation. In addition, the automatic and manual measurements were not significantly different (p-value > 0.05) for variations of FOV and pitch.

Evaluation of silicone rubber-lead shield's effectiveness in protecting the breast during thoracic CT.

Radiation of thoracic computed tomography (CT) involves the breast although it is not considered an organ of interest. According to the International Commission on Radiological Protection (ICRP) No. 103, the breast is an organ with a high level of sensitivity when interacting with x-rays, increasing the potential risk of breast cancer. Therefore, the radiation dose must be optimized while maintaining image quality. The dose optimization can be accomplished using a radiation shield. This study aims to determine the effect of silicone rubber (SR)-lead (Pb) in various thicknesses as an alternative protective material limiting dose and preserving the image quality of the breast in thoracic CT. SR-Pb was made from SR and Pb by a simple method. The SR-Pb had thicknesses of 3, 6, 9, and 12 mm. The breast dose was measured using a CT dose profiler on the surface of the breast phantom. The CT number and the noise level of the resulting image were determined quantitatively. The dose without the radiation shield was 5.4 mGy. The doses measured using shielding with thicknesses of 3, 6, 9, and 12 mm were 5.2, 4.5, 4.3, and 3.3 mGy, respectively. Radiation shielding with a thickness of 12 mm reduced breast surface dose by up to 38%. The CT numbers and noise levels for the left and right breast phantom images were almost the same as those ​​without radiation shields indicating there were only slight artifacts in the image. Therefore, SR-Pb is considered a good shielding material which can be pplied in a clinical setting by placing it directly on the breast surface for dose optimization.

Identification of the computed tomography dose index for tube voltage variations in a polyester-resin phantom.

The aim of this study is to measure the volumetric computed tomography dose index (CTDIvol) for different tube voltages for a polyester-resin (PESR) phantom, and to compare it to values for a standard polymethyl methacrylate (PMMA) phantom. Both phantoms are head phantoms with a diameter of 16 cm. The phantoms were scanned by a CT scanner (GE Revolution EVO 64/128 slice) with tube voltages of 80, 100, 120, and 140 kV. The other scan parameters were constant (i.e. tube current of 100 mA, rotation time of 1 s, and collimation width of 10 mm). The CTDI100,c and CTDI100,p were obtained by measuring the dose with an ionization chamber inserted into five holes within the phantoms. The CTDIvol was calculated based on the CTDI100,c and CTDI100,p values. The measurements were repeated three times for each hole. It was found that the CTDIvol values for the PESR phantom were dependent on tube voltage value, and were similar to the dependency in a PMMA phantom. The maximum CTDIvol difference between the PESR and PMMA phantoms was 7.5%. We conclude that the dose measured in the PESR phantom is similar to that in the PMMA phantom and that the PESR phantom can be used as an alternative if the PMMA phantom is not available.